IEEE transactions on pattern analysis and machine intelligence
Apr 3, 2024
Achieving human-level dexterity in robotics remains a critical open problem. Even simple dexterous manipulation tasks pose significant difficulties due to the high number of degrees of freedom and the need for cooperation among heterogeneous agents (...
IEEE transactions on pattern analysis and machine intelligence
Apr 3, 2024
Neural Architecture Search (NAS), aiming at automatically designing neural architectures by machines, has been considered a key step toward automatic machine learning. One notable NAS branch is the weight-sharing NAS, which significantly improves sea...
IEEE transactions on pattern analysis and machine intelligence
Mar 8, 2024
Large foundational models, through upstream pre-training and downstream fine-tuning, have achieved immense success in the broad AI community due to improved model performance and significant reductions in repetitive engineering. By contrast, the tran...
IEEE transactions on pattern analysis and machine intelligence
Dec 5, 2023
Eye gaze analysis is an important research problem in the field of Computer Vision and Human-Computer Interaction. Even with notable progress in the last 10 years, automatic gaze analysis still remains challenging due to the uniqueness of eye appeara...
IEEE transactions on pattern analysis and machine intelligence
Dec 5, 2023
Ensuring safety and achieving human-level driving performance remain challenges for autonomous vehicles, especially in safety-critical situations. As a key component of artificial intelligence, reinforcement learning is promising and has shown great ...
IEEE transactions on pattern analysis and machine intelligence
Nov 3, 2023
Contrastive learning, which aims to capture general representation from unlabeled images to initialize the medical analysis models, has been proven effective in alleviating the high demand for expensive annotations. Current methods mainly focus on in...
IEEE transactions on pattern analysis and machine intelligence
Oct 4, 2023
Defining the loss function is an important part of neural network design and critically determines the success of deep learning modeling. A significant shortcoming of the conventional loss functions is that they weight all regions in the input image ...
IEEE transactions on pattern analysis and machine intelligence
Oct 3, 2023
Deep learning architectures, albeit successful in most computer vision tasks, were designed for data with an underlying Euclidean structure, which is not usually fulfilled since pre-processed data may lie on a non-linear space. In this article, we pr...
IEEE transactions on pattern analysis and machine intelligence
Aug 7, 2023
Histopathological Whole Slide Images (WSIs) play a crucial role in cancer diagnosis. It is of significant importance for pathologists to search for images sharing similar content with the query WSI, especially in the case-based diagnosis. While slide...
IEEE transactions on pattern analysis and machine intelligence
Jun 30, 2023
Pairwise learning is receiving increasing attention since it covers many important machine learning tasks, e.g., metric learning, AUC maximization, and ranking. Investigating the generalization behavior of pairwise learning is thus of great significa...